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Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study

BACKGROUND: Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns...

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Autores principales: Tilly, Martijn J., Lu, Zuolin, Geurts, Sven, Ikram, M. Arfan, Stricker, Bruno H., Kors, Jan A., de Maat, Moniek P. M., de Groot, Natasja M. S., Kavousi, Maryam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241730/
https://www.ncbi.nlm.nih.gov/pubmed/35948741
http://dx.doi.org/10.1007/s00392-022-02071-6
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author Tilly, Martijn J.
Lu, Zuolin
Geurts, Sven
Ikram, M. Arfan
Stricker, Bruno H.
Kors, Jan A.
de Maat, Moniek P. M.
de Groot, Natasja M. S.
Kavousi, Maryam
author_facet Tilly, Martijn J.
Lu, Zuolin
Geurts, Sven
Ikram, M. Arfan
Stricker, Bruno H.
Kors, Jan A.
de Maat, Moniek P. M.
de Groot, Natasja M. S.
Kavousi, Maryam
author_sort Tilly, Martijn J.
collection PubMed
description BACKGROUND: Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women. METHODS: Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into ‘single-documented AF episode’, ‘multiple-documented AF episodes’, or ‘long-standing persistent AF’. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis. RESULTS: We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as ‘single-documented AF episode’, 208 (1.5%) as ‘multiple-documented AF episodes’, and 57 (0.4%) as ‘long-standing persistent AF’. In men, we found poorer trajectories of weight and waist circumference preceding ‘long-standing persistent AF’ as compared to the other patterns. In women, we found worse trajectories of all risk factors between ‘long-standing persistent AF’ and the other patterns. CONCLUSION: We developed a standardized method to classify AF patterns in the general population. Participants categorized as ‘long-standing persistent AF’ showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns. GRAPHICAL ABSTRACT: [Image: see text]
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spelling pubmed-102417302023-06-07 Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study Tilly, Martijn J. Lu, Zuolin Geurts, Sven Ikram, M. Arfan Stricker, Bruno H. Kors, Jan A. de Maat, Moniek P. M. de Groot, Natasja M. S. Kavousi, Maryam Clin Res Cardiol Original Paper BACKGROUND: Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women. METHODS: Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into ‘single-documented AF episode’, ‘multiple-documented AF episodes’, or ‘long-standing persistent AF’. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis. RESULTS: We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as ‘single-documented AF episode’, 208 (1.5%) as ‘multiple-documented AF episodes’, and 57 (0.4%) as ‘long-standing persistent AF’. In men, we found poorer trajectories of weight and waist circumference preceding ‘long-standing persistent AF’ as compared to the other patterns. In women, we found worse trajectories of all risk factors between ‘long-standing persistent AF’ and the other patterns. CONCLUSION: We developed a standardized method to classify AF patterns in the general population. Participants categorized as ‘long-standing persistent AF’ showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns. GRAPHICAL ABSTRACT: [Image: see text] Springer Berlin Heidelberg 2022-08-10 2023 /pmc/articles/PMC10241730/ /pubmed/35948741 http://dx.doi.org/10.1007/s00392-022-02071-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Tilly, Martijn J.
Lu, Zuolin
Geurts, Sven
Ikram, M. Arfan
Stricker, Bruno H.
Kors, Jan A.
de Maat, Moniek P. M.
de Groot, Natasja M. S.
Kavousi, Maryam
Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study
title Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study
title_full Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study
title_fullStr Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study
title_full_unstemmed Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study
title_short Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study
title_sort atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the rotterdam study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241730/
https://www.ncbi.nlm.nih.gov/pubmed/35948741
http://dx.doi.org/10.1007/s00392-022-02071-6
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